Senior Data Engineer - Remote

Position Purpose

Renown Health is looking for a Senior Data Engineer familiar with the Microsoft Azure Cloud-based platform, both traditional as well as Fabric. This position will develop, design, implement, and maintain a Microsoft Azure Data Warehousing environment and help architect the Enterprise Data Warehouse for all corporate entities of Renown Health. The role will include setting up and automating data pipelines via ETL / ELT processes with internal departments and external third parties, verifying data accuracy, and optimizing the data environments to enable the work of data scientists and analysts. The engineer will be expected to know SQL and be comfortable discussing complex computer science or statistical concepts with data scientists and analysts. Innovation is critical to this role as an ideal candidate will possess the ability to lead the development of a cloud-based enterprise data warehouse, along with engineering solutions to support the development of new reporting systems, analytic engines, and machine learning algorithms.

Nature and Scope

This role can be either remote or hybrid.

Primary Responsibilities:

• In collaboration with Team members, build full technology stack of services for commercialization purposes including PaaS (Platform as-a-service), IaaS (Infrastructure as-a-service), SaaS (software as-a-service), operations and management.

• Manage and optimize the movement and validation of data from an Epic EMR system to Renown Health’s Enterprise Data Warehouse (EDW).

• Accountable for data engineering lifecycle including research, proof of concepts, architecture, design, development, test, deployment, and maintenance.

• Oversee the development of novel data pipelines that integrate and normalize large data from a variety of sources (e.g., electronic health record, claims, wearable device, publicly available data, etc.) to enable learning health, machine learning model development, and deployment.

• Design, direct and implement ETL processes, including data capture, data quality, testing and validation methods.

• Knowledge of interface engines and protocols. Experience with HL7, X12 and/or XML and OPENLink.

• Provide guidance on synchronizing the Epic EMR data architecture with customized data models that facilitate reporting and analytics.

• Layer in instrumentation in the development process so that data pipelines can be monitored. Measurements are used to detect internal problems before they result into user visible outages or data quality issues.

• Build processes and diagnostic tools to troubleshoot, maintain and optimize engineering environments and respond to production issues.

• Provide subject matter expertise and hands on delivery of data capture, curation, and consumption pipelines for Microsoft Azure.

• Ability to build Azure data solutions and provide technical perspective on storage, big data platform services, serverless architectures, Hadoop ecosystem, vendor products, RDBMS, DW/DM, NoSQL databases and security.

• Participate in deep architectural discussions to build confidence and ensure customer success when building new solutions and migrating existing data applications on the Azure platform.

• Develop documentation, such as data dictionaries, guides, or data flow diagrams that assists staff in identifying, locating, and using the organization’s data.

Incumbent Must Possess:

• Minimum of 3 years of SQL programming experience and associated SQL tools (SSIS, SSMS, SSRS, etc.).

• Experience with Visual Studio is preferred.

• At least 3 years of experience in developing data ingestion, data processing and analytical pipelines for big data, relational databases, NoSQL and data warehouse solutions.

• Minimum of 3 years of RDBMS experience.

• Extensive hands-on experience implementing data migration and data processing using Azure services: ADLS, Azure Data Factory, Azure Functions, Synapse/DW, Azure SQL DB, Event Hub, IOT Hub, Azure Stream Analytics, Azure Analysis Service, HDInsight, Databricks Azure Data Catalog, Cosmo Db, ML Studio, AI/ML, etc.

Some experience with AWS and related Amazon cloud technologies is desirable.

• Familiarity of the environments needed to facilitate the work of data scientists and analysts in healthcare.

• Knowledge of medical terminology, especially ICD-10 codes, CPT codes, DRG codes, and an understanding of adjudicated claims data.

• Excellent verbal and written communication. An applicant may be asked to provide examples of written work to demonstrate technical writing proficiency.